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Esch, Barbara E.; Lindblad, Tracie L.; Clark, Brittany; Ali, Zareen – Analysis of Verbal Behavior, 2023
An intraverbal assessment was administered to older adults with aphasia, using a hierarchy of questions that required increasingly complex verbal discriminative stimulus control. Five categories of errors were defined and analyzed for putative stimulus control, with the aim to identify requisite assessment components leading to more efficient and…
Descriptors: Aphasia, Brain, Injuries, Error Analysis (Language)
Daniel Freudenthal; Fernand Gobet; Julian M. Pine – Language Learning, 2024
This study extended an existing crosslinguistic model of verb-marking errors in children's early multiword speech (MOSAIC) by adding a novel mechanism that defaults to the most frequent form of the verb where this accounts for a high proportion of forms in the input. Our simulations showed that the resulting model not only provides a better…
Descriptors: Contrastive Linguistics, Error Analysis (Language), Native Language, Verbs
Misato Hiraga – ProQuest LLC, 2024
This dissertation developed a new learner corpus of Japanese and introduced an error and linguistic annotation scheme specifically designed for Japanese particles. The corpus contains texts written by learners who are in the first year to fourth year university level Japanese courses. The texts in the corpus were tagged with part-of-speech and…
Descriptors: Japanese, Computational Linguistics, Form Classes (Languages), Error Analysis (Language)
Lidster, Ryan – ProQuest LLC, 2023
When acquiring a second language, learners must become able to perceive the difference between novel sounds ("discrimination") and also associate strings of sounds with distinct vocabulary items ("lexical encoding"). Recent research has questioned whether discrimination is a sufficient or necessary condition for encoding, and…
Descriptors: Language Processing, Japanese, Second Language Learning, Second Language Instruction
Dongkawang Shin; Yuah V. Chon – Language Learning & Technology, 2023
Considering noticeable improvements in the accuracy of Google Translate recently, the aim of this study was to examine second language (L2) learners' ability to use post-editing (PE) strategies when applying AI tools such as the neural machine translator (MT) to solve their lexical and grammatical problems during L2 writing. This study examined 57…
Descriptors: Second Language Learning, Second Language Instruction, Translation, Computer Software

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